Design and Development of Efficient Energy Systems

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There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.
This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.
The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.

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The first step of the proposed system is to detect sewer gas level. A gas sensor can be used to detect the level of the gas. The level of Carbon Monoxide, Hydrogen sulphide and Methane has been measured using a gas sensor. The sensor data is fed to the proposed Tristate pattern. This pattern trains the data based on continues 3 ones and predicts the threshold for each gas. If the level exceeds the threshold value then it gives the alert.

3.3.1.1 Proposed Tristate Pattern

The gas sensor data is given to the input of the proposed system. The proposed system provides 1 for 3 consequent ones and .5 for 2 consequent ones and .25 for one. The Table 3.1below shows the structure of the Tristate pattern.

Table 3.1 Tristate pattern.

Patterns Score
Consequent 3 ones 3
Consequent 2 ones 2
Single one 1

Finally, the sum of the values has been calculated using the formula below:

Where CHM denotesCarbon Monoxide Hydrogen sulphide and Methane sensor datas - фото 40

Where C,H,M denotesCarbon Monoxide, Hydrogen sulphide and Methane sensor datas and n,m, p denotes the range of the datas.

All these major components are connected in the arduino board with connecting wires and fitted in the required places (underground drainage pipes) where damaged occurred. It will easily detect the gases and also the leakage of pipes in that specific area. It also gives a notification to the authorities about the leakage by a message and it is able to identify the location by GSM module and fix the problem as soon as possible.

3.3.2 Crack Detection

A semi-automated battery-operated ( Figure 3.2) cart is designed with ultrasonic sensors attached to the front. This ultrasonic sensor sends high-frequency sound waves through the transmitter head, which then goes and reflects back on hitting the surface of the track, and comes back to the receiver head. This is then converted to distance.

A threshold distance is set, by measuring the distance between the sensor and the surface of the track. At the time of inspection, if the distance exceeds or is less than the threshold distance, it indicates that a crack is present on the track. When a crack as such is detected, the cart stops there. This is the first level of testing.

As a second level of testing, once the cart stops, a camera attached to the front of the cart is triggered on. This camera then takes a picture of the track where the crack is present. This picture is then sent to the Amazon S3 bucket and image processing is performed on the captured image. This is done so as to detect if it is a major or a minor crack.

In case of a major crack, the cart will store the GPS location and return to the previous checkpoint. In case of a minor crack, the cart will continue with its inspection. In either case, the GPS location and the details of the crack and the status are stored in Amazon EC2 and are sent immediately to the concerned authorities to be rectified as soon as possible.

Figure 32 Flow diagram of the automated system Cart development and sensor - фото 41

Figure 3.2 Flow diagram of the automated system.

Cart development and sensor:

For the development of the cart, 12V DC motors can be used. Motor controller L298N is used to control the movement of the cart. Ultrasonic sensor HC-SR04 sends high-frequency sound waves and calculates the distance of the reflected wave. This sensor detects the minute defects with high accuracy. This is a non-destructive testing method.

Raspberry Pi 3:

RPi is a low-cost, small credit-card-sized computer. RPi3 is faster than Arduino.

Cloud server and Image processing:

Host server is AWS EC2. Date, time, message status, ID, sensor value, latitude and longitude are stored in the EC2 database. A picture of the defect is taken and stored in AWS S3 bucket. Gaussian Mixture Model can be used for image processing which comes under supervised learning.

3.3.3 Experimental Setup

Gas Sensor

A gas sensor ( Figure 3.3) is utilized to identify the nearness of a hazardous LPG spill in a vehicle or in a work station, stockpiling tank condition. This unit is frequently effectively fused into a caution unit, to sound an alert or give a visual sign of the LPG fixation. The sensor has excellent affectability joined with a quick repsonse time. The sensor likewise can detect iso-butane, propane, LNG and tobacco smoke.

Ultrasonic Sensor

Ultrasonic robots for break location contain transducers arranged at an alternate point to the channel divider. This guarantees ultrasonic shear waves spread along a 45° way through the divider. Both inward and outside splits mirror the vitality.

GPS

The GPS module L10 brings the superior of the MTK situating motor to the monetary norm. The L10 bolsters 210 PRN channels. This adaptable, independent recipient consolidates a careful exhibit of highlights with adaptable availability choices. Their straightforward combination prompts quick time-to-advertise during a wide determination of car, customer and modern applications.

Figure 33 Gas sensor Raspberry Pi Raspberry Pi board Figure 34 is a - фото 42

Figure 3.3 Gas sensor.

Raspberry Pi

Raspberry Pi board ( Figure 3.4) is a small wonder, pressing extensive registering power into an impression no bigger than a Mastercard. It’s prepared to do some stunning things; however, there are a couple of things that the user needs to know before using it. The processor at the core of the Raspberry Pi framework is a Broadcom BCM2835 framework on-chip (SoC) interactive media processor. This implies most by far of the framework’s segments, including its focal and illustrations handling units alongside the sound and interchanges equipment, are fabricated onto that solitary segment covered up underneath the 256 MB memory chip at the focal point of the board It’s not simply this SoC plan that makes the BCM2835 distinctive to the processor found in a work area or PC, notwithstanding. It likewise utilizes an alternate guidance set engineering (ISA), known as ARM.

GSM Module (Global System for Mobile Communications):

GSM is an open and computerized cell innovation utilized for transmitting portable voice and information administrations works at the 850MHz, 900MHz, 1800MHz and 1900MHz recurrence groups. GSM framework was created as a computerized framework utilizing time division different access (TDMA) strategy for correspondence reason. Figure 3.5presents a flow diagram of the leakage detection.

Figure 34 Raspberry pi Figure 35 Flow diagram of the leakage detection - фото 43

Figure 3.4 Raspberry pi.

Figure 35 Flow diagram of the leakage detection Mobile Application A - фото 44

Figure 3.5 Flow diagram of the leakage detection.

Mobile Application:

A portable application, usually alluded to as an application, is a sort of use programming intended to run on a cell phone, for example, or tablet PC. Portable applications as often as possible serve to give clients comparative administrations to those found on PCs. Applications are commonly little, singular programming units with constrained capacity. This utilization of application programming was initially promoted by Apple Inc. Its App Store offers a large number of utilizations for the iPhone, iPad and iPod Touch.

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